Project Name

Overview

This is a starter kit for my Machine Learning project. It provides a structured directory layout, pre-defined scripts, and configurations to help you quickly set up and start working on your ML project.

Project Structure

.
├── bin/                     # Binary files or scripts
├── data/                    # Data storage
│   └── .gitkeep             # Keeps the folder in version control
├── notebook/                # Jupyter notebooks for experiments and analysis
│   └── .gitkeep             # Keeps the folder in version control
├── results/                 # Output results from experiments
│   └── .gitkeep             # Keeps the folder in version control
├── src/                     # Source code for the project
│   ├── configs/              # Configuration files
│   │   └── .gitkeep         # Keeps the folder in version control
│   ├── eval/                # Evaluation scripts
│   │   └── __init__.py
│   ├── experiments/         # Experiment scripts and logs
│   │   └── .gitkeep         # Keeps the folder in version control
│   ├── finetune/            # Fine-tuning scripts
│   │   └── __init__.py
│   ├── inference/           # Inference scripts
│   │   ├── inference.py
│   │   └── __init__.py
│   ├── models/              # Model definitions
│   │   ├── models.py
│   │   └── __init__.py
│   ├── train/               # Training scripts
│   │   ├── train.py
│   │   └── __init__.py
│   ├── utils/               # Utility scripts
│   │   ├── prepare_data.py
│   │   └── __init__.py
│   └── __init__.py
├── scripts/                 # Scripts for setting up and running the project
│   └── run.sh
├── requirements.txt         # Python dependencies
├── .gitignore               # Git ignore file
├── CONTRIBUTING.md          # Guidelines for contributing to the project
├── LICENSE                  # License file
└── README.md                # Project documentation

Getting Started

1. Clone the repository:

   git clone <repository-url>
   cd <repository-directory>

2. Install dependencies:

   pip install -r requirements.txt

3. Run the project: Use the provided scripts in the scripts/ directory to start training, evaluation, or inference.

Contributing

Please read CONTRIBUTING.md for guidelines on how to contribute to this project.

License

This project is licensed under the MIT License - see the LICENSE file for details.